Launching today
DataChef MUS
Feedback that lives where your users interpret output
3 followers
Feedback that lives where your users interpret output
3 followers
Users look at your output and form opinions, strong ones. By the time they find a way to say so, all the context is gone. MUS puts the reaction exactly where the interpretation happens. One component. No forms.
Hey PH 👋
We built MUS while shipping AI-powered data products at DataChef, and we kept hitting the same wall 🚀
Users would look at an AI-generated summary or a model recommendation and have real opinions about it. But by the time they found a way to surface that feedback, all the context was gone. We'd get a Slack message: "that forecast looks off", no reference to which section, which run, or what exactly triggered it.
So we asked a simple question: what if the feedback lived exactly where the interpretation happens?
That's MUS. You wrap any output, a summary, a chart, a score, a recommendation with , and your users get a hover toolbar right there. Thumbs, voice notes, a direct Slack thread, even a recorded video walkthrough for the section. Nothing leaves the context of what they're reacting to.
The thing we're most proud of: it's genuinely low-friction for users. No forms. No context switching. A 30-second voice clip captures more signal than three paragraphs typed into a feedback widget ever did.
MIT licensed, self-hostable with a single Docker sidecar, and routes to Slack, Discord, Teams, or any webhook.
If you're building products where users interpret, question, or act on output, that's exactly who we built this for. Happy to answer anything.